ncpol2sdpa 1.1

Ncpol2sdpa

Ncpol2sdpa is a set of scripts to convert a polynomial optimization problem of either commutative or noncommutative variables to a sparse semidefinite programming (SDP) problem that can be processed by the SDPA family of solvers. The optimization problem can be unconstrained or constrained by equalities and inequalities.

The objective is to be able to solve very large scale optimization problems. For example, a convergent series of lower bounds can be obtained for ground state problems with arbitrary Hamiltonians.

The implementation has an intuitive syntax for entering Hamiltonians and it scales for a larger number of noncommutative variables using a sparse representation of the SDP problem.

Dependencies

The code requires SymPy>=0.7.2 in the Python search path. The code is known to work with Python 2.6.8 and 2.7.5, and also with Pypy 1.8 and 2.0.2. Using Pypy is highly recommended, as execution time is several times faster and memory use is reduced. The code is compatible with Python 3, but using Python 3.3.2 incurs a major decrease in performance; the case is likely to be similar in with other Python 3 versions.